tanstack-ranger
Provides headless utilities for implementing range and multi-range sliders. Supports TS/JS, React, Vue, Solid, Svelte, and Angular.
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Find your next superpower If you are an agent, refer to our llms.txt for full access.Provides headless utilities for implementing range and multi-range sliders. Supports TS/JS, React, Vue, Solid, Svelte, and Angular.
Provides type-safe application routing for React and Solid. Includes first-class search parameter handling, data loading, and integration with the React ecosystem.
Generates a complete TanStack Start application with server rendering, file-based routing, and server functions. Integrates D1 with Drizzle, better-auth, Tailwind v4, and shadcn/ui, creating project files without a template repository.
Provides a full-stack React framework powered by TanStack Router. Supports server-side rendering, streaming, server functions, and deployment to any hosting provider.
Provides an immutable reactive data store independent of any UI framework. Includes adapters for React, Vue, Solid, Angular, and Svelte.
Provides headless UI utilities for creating tables and data grids. Supports TS/JS, React, Vue, Solid, Svelte, Qwik, Angular, and Lit.
Provides headless UI for virtualizing large element lists at 60 FPS. Supports TS/JS, React, Vue, Solid, Svelte, Lit, and Angular.
Performs root cause analysis on classification experiments and AOI defect-detection pipelines. Investigates poor recall, false acceptance rates, PASS/NO_PASS metrics, and prediction regressions, with RCA reporting.
Runs gap analysis through a pinned TAO data-services container. Selects a decision threshold and exports the weakest samples in a parquet dataset expanded by lighting condition for downstream augmentation.
Analyzes prediction JSON for yes/no visual question classification workflows. Identifies failure cases for downstream DEFT root cause analysis.
Runs format conversion for datasets supported by NVIDIA TAO DAFT. Applies specifically to DAFT data rather than general dataset conversion.
CLIP vision-language model for image-text retrieval, zero-shot classification, embedding extraction, ONNX export, and TensorRT deployment. Use when fine-tuning or training CLIP, running zero-shot classification, computing image embeddings, or deploying CLIP to ONNX/TensorRT. This is a single-action model skill; do not use it for an iterative weak-attribute improvement loop that keeps retraining an…
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